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Mutational Signatures in Upper Tract Urothelial Carcinoma Define Etiologically Distinct

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Mutational Signatures in Upper Tract Urothelial Carcinoma Define Etiologically Distinct bioRxiv preprint doi: https://doi.org/10.1101/735324; this version posted August 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 1 Mutational signatures in upper tract urothelial carcinoma define etiologically distinct 2 subtypes with prognostic relevance 3 Xuesong Li1†, Huan Lu2,3†, Bao Guan 1,2,4,5†, Zhengzheng Xu2,3, Yue Shi2, Juan Li2,3, Wenwen 4 Kong2,3, Jin Liu6, Dong Fang1,5, Libo Liu1,4,5, Qi Shen1,4,5, Yanqing Gong1,4,5, Shiming He1,4,5, Qun 5 He1,4,5, Liqun Zhou 1,4,5* and Weimin Ci 2,3,7* 6 Affiliations: 7 1Department of Urology, Peking University First Hospital, Beijing 100034, China. 8 2Key Laboratory of Genomics and Precision Medicine, Beijing Institute of Genomics, Chinese 9 Academy of Sciences, Beijing 100101, China; 10 3University of Chinese Academy of Sciences, Beijing 100049, China. 11 4Institute of Urology, Peking University, Beijing 100034, China. 12 5National Urological Cancer Center, Beijing, 100034, China. 13 6Department of Urology, The Third Hospital of Hebei Medical University, Hebei 050051, China. 14 7Institute of Stem cell and Regeneration, Chinese Academy of Sciences, Beijing 100101, China. 15 16 *Correspondence to: [email protected]; and [email protected]. 17 † These authors contributed equally to this work. 18 19 Keywords: 20 Upper tract urothelial carcinoma; Whole-genome sequencing; Mutational signature; Aristolochic 21 acid. 22 23 1 bioRxiv preprint doi: https://doi.org/10.1101/735324; this version posted August 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 24 Abstract 25 Parts of East Asia have a very high upper tract urothelial carcinoma (UTUC) prevalence, and an 26 etiological link between the medicinal use of herbs containing aristolochic acid (AA) and UTUC 27 has been established. The mutational signature of AA, which is characterized by a particular 28 pattern of A:T to T:A transversions, can be detected by genome sequencing. Thus, integrating 29 mutational signatures analysis with clinicopathological data may be a crucial step toward 30 personalized treatment strategies for the disease. Therefore, we performed whole-genome 31 sequencing (WGS) of 90 UTUC patients from China. Mutational signature analysis via 32 nonnegative matrix factorization method defined three etiologically distinct subtypes with 33 prognostic relevance: (i) AA, the typical AA mutational signature characterized by signature 22, 34 had the highest tumor mutation burden, the best clinical outcomes; (ii) Age, an age-related group 35 featured by signatures 1 and 5, had the lowest weighted genome instability index score, the worst 36 clinical outcomes; and (iii) DSB, signature with deficiencies in DNA double strand break-repair 37 featured by signatures 3, the intermediate clinical outcomes. Additionally, the distinct AA subtype 38 was associated with AA exposure, the highest number of predicted neoantigens and heavier 39 lymphocytes infiltrating. Thus, it may be good candidate for immune checkpoint blockade therapy. 40 Notably, we showed AA-mutational signature was also identified in histologically “normal” 41 urothelial cells. Thus, non-invasive urine test based on the AA-mutational signature could take 42 advantage of this “field effect” to screen individuals at increased risk of recurrence due to exposure 43 to herbal remedies containing the carcinogen AA. Collectively, the findings here may accelerate 44 the development of novel prognostic markers and personalized therapeutic approaches for UTUC 45 patients in China. 46 2 bioRxiv preprint doi: https://doi.org/10.1101/735324; this version posted August 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 47 Introduction 48 The epidemiology and clinicopathological characteristics of UTUC is largely influenced by its 49 geographic distribution. Parts of East Asia such as Taiwan have a much higher UTUC prevalence, 50 accounting for more than 30% of urothelial cancers (UCs)(1-3) compared to only 5-10% of UCs 51 in Western populations(4). Chinese patients are more frequently female, of higher rate for kidney 52 failure(5). Conceivably, geographic differences in risk factors for UTUC, such as AA-containing 53 herb drugs consumption may account for some of these observations(1, 6-8). It has been shown 54 that AA-induced mutational signature was characterized by A:T to T:A transversions at the 55 sequence motif A[C∣T]AGG(8, 9). The unusual genome-wide AA signature, termed signature 56 22 in COSMIC, holds great potential as “molecular fingerprints” for AA exposure in multiple 57 cancer types(7, 9). Similarly, other endogenous or exogenous DNA damaging agents will also 58 create mutational signatures detectable by DNA sequencing(10). Thus, analyses of mutational 59 signatures, informative in other tumors(11, 12), have not been comprehensively reported in UTUC 60 especially Chinese patients. The most comprehensive genomic studies of UTUC in Western 61 populations used exome sequencing or targeted panel sequencing of cancer-associated genes(13- 62 15). However, deriving signatures from whole-exome data may be problematic(16). Herein, we 63 reported the first comprehensive genomic analysis of UTUC based on mutational signatures using 64 WGS in 90 Chinese UTUC patients. Mutational signature analysis defined three UTUC subtypes 65 with distinct etiologies and clinical outcomes. We further showed that geographically distinct AA 66 subtype with high tumor mutation burden and higher level of tumor-infiltrating lymphocytes held 67 great potential for immunotherapy. These results provided deeper insights into the biology of this 68 cancer. 69 3 bioRxiv preprint doi: https://doi.org/10.1101/735324; this version posted August 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 70 Results 71 Copy number variations (CNVs) dominate the UTUC landscape 72 The flowchart of selecting patients was shown in fig. S1. Clinicopathologic characteristics of 90 73 UTUC patients were listed in table S1. The samples were sequenced by WGS to an average 30X 74 depth which allowed us to comprehensively catalog both single nucleotide variations (SNVs), 75 small insertions and deletions (indels) and copy number variations (CNVs). We identified a 76 median of 19,639 (interquartile range [IQR], 16,578 to 32,937) SNVs and a median of 2,197 (IQR, 77 1,615 to 2,650) indels. A median of 437 (IQR, 355 to 584) coding mutations was noted (fig. 1A). 78 The increased mutation load was consistent with the increased prevalence of exposure to the potent 79 mutagen AAs (fig. 1B). Next, we examined the candidate driver genes with MutSigCV (Q<0.05). 80 Only two genes, TP53 and FRG2C, were identified (fig. 1C). However, many genes listed in the 81 Cancer Gene Census as known driver genes were affected by non-silent mutations including genes 82 which frequently mutated in Western UTUC patients, such as KMT2D (18%) and ARID1A (14%) 83 (fig. 1C). Additionally, the overall genomic landscape confirmed the dominance of recurrent 84 CNVs compared with SNVs and indels in the cohort (fig. 1D). 85 Mutational signatures define three UTUC subtypes with distinct etiology 86 Next, we explored the dynamic interplay of risk factors and cellular processes using mutational 87 signature analysis. We identified 23 mutational signatures defined by COSMIC in our cohort, 88 which were merged by shared aetiologies into 9 signatures by MutationalPatterns(17) (Materials 89 and Methods). Hierarchical clustering based on the number of SNVs attributable to each signature 90 confirmed three major subtypes (fig. 2A): (1) AA, there is significantly higher number of signature 91 22(1, 8) mutations (a median of 1,871 ) compared to the other two subtypes (fig. 2B, Wilcoxon 92 rank test); (2) Age, there is significantly higher number of signatures 1 and 5, attributed to clocklike 4 bioRxiv preprint doi: https://doi.org/10.1101/735324; this version posted August 15, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder. All rights reserved. No reuse allowed without permission. 93 mutational processes accumulated over cell divisions(18) (fig. 2C, Wilcoxon rank test); and (3) 94 DSB, there is significantly higher number of signature 3 mutations, associated with failure of DNA 95 double-strand break-repair by homologous recombination (fig. 2D, Wilcoxon rank test). We 96 further verified whether the subtypes defined by mutational signatures associated with their 97 attributed etiological and clinicopathologic features. Consistent with previous epidemiological 98 studies in Asian patients(6, 19-21), we found that the AA subtype was significantly associated 99 with AA-containing herb drugs intake, poor renal function, female sex, multifocality and lower T 100 stage (fig. 2E, Kruskal-Wallis test). Thus, the AA subtype defined by mutational signatures did 101 capture the etiological subgroup of UTUC patients who had AAs exposure. Furthermore, 102 consistent with the scenario that DNA damage repair deficiency may increase genomic instability, 103 the DSB subtype exhibited both higher level weighted genome integrity index (wGII) and higher 104 level microsatellite instability (MSI) compared to the Age subtype (fig. 2F and 2G). Additionally, 105 lymphovascular invasion, an independent predictor of clinical outcomes for UTUC(22), was 106 higher in the Age subtype compared to the DSB subtype. Although statistically significance was 107 not achieved which may be due to limited number of cases (table S2). 108 Subtypes defined by mutational signatures can predict clinical outcomes 109 Next, we explored whether clinical outcomes of the three subtypes differed significantly. Notably, 110 a Kaplan-Meier plot revealed that the subtypes can predict both cancer-specific survival (CSS) 111 (fig.
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